时滞惯性神经网络的稳定性和分岔控制

Stability and bifurcation control in inertial neuron networks with delays

针对一类二阶时滞惯性神经网络模型,提出一种基于时滞反馈的分岔控制方法.利用时滞微分方程动力学理论,给出反馈控制系统的稳定性以及发生Hopf分岔的判别条件.数值仿真显示所设计的控制器不仅能有效延迟网络分岔的发生,还能扩大稳定域并改善网络的收敛速度.

Based on the second order delay inertia neural network model, this paper puts forward the bifurcation control method： delay feedback control method. Applying the theory of delay differential equations, we give some stability and Hopf bifurcation conditions for the feedback control system. Examples are given to validate that the feedback controller can control the occurrence of bifurcation effectively, expand the stability domain, and change the convergence speed of the network as well.